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Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.07

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Content: Vgl.: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CEAQFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.91.4940%26rep%3Drep1%26type%3Dpdf&ei=dOXrUMeIDYHDtQahsIGACg&usg=AFQjCNHFWVh6gNPvnOrOS9R3rkrXCNVD-A&sig2=5I2F5evRfMnsttSgFF9g7Q&bvm=bv.1357316858,d.Yms.
Date: 8. 1.2013 10:22:32

Zhou, G.D.; Zhang, M.; Ji, D.H.; Zhu, Q.M.: Hierarchical learning strategy in semantic relation extraction (2008) 0.03

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Subramanian, S.; Shafer, K.E.: Clustering (2001) 0.02

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Date: 5. 5.2003 14:17:22

Schek, M.: Automatische Klassifizierung und Visualisierung im Archiv der Süddeutschen Zeitung (2005) 0.02
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Abstract

Die Süddeutsche Zeitung (SZ) verfügt seit ihrer Gründung 1945 über ein Pressearchiv, das die Texte der eigenen Redakteure und zahlreicher nationaler und internationaler Publikationen dokumentiert und auf Anfrage für Recherchezwecke bereitstellt. Die Einführung der EDV begann Anfang der 90er Jahre mit der digitalen Speicherung zunächst der SZ-Daten. Die technische Weiterentwicklung ab Mitte der 90er Jahre diente zwei Zielen: (1) dem vollständigen Wechsel von der Papierablage zur digitalen Speicherung und (2) dem Wandel von einer verlagsinternen Dokumentations- und Auskunftsstelle zu einem auch auf dem Markt vertretenen Informationsdienstleister. Um die dabei entstehenden Aufwände zu verteilen und gleichzeitig Synergieeffekte zwischen inhaltlich verwandten Archiven zu erschließen, gründeten der Süddeutsche Verlag und der Bayerische Rundfunk im Jahr 1998 die Dokumentations- und Informationszentrum (DIZ) München GmbH, in der die Pressearchive der beiden Gesellschafter und das Bildarchiv des Süddeutschen Verlags zusammengeführt wurden. Die gemeinsam entwickelte Pressedatenbank ermöglichte das standortübergreifende Lektorat, die browserbasierte Recherche für Redakteure und externe Kunden im Intraund Internet und die kundenspezifischen Content Feeds für Verlage, Rundfunkanstalten und Portale. Die DIZPressedatenbank enthält zur Zeit 6,9 Millionen Artikel, die jeweils als HTML oder PDF abrufbar sind. Täglich kommen ca. 3.500 Artikel hinzu, von denen ca. 1.000 lektoriert werden. Das Lektorat erfolgt im DIZ nicht durch die Vergabe von Schlagwörtern am Dokument, sondern durch die Verlinkung der Artikel mit "virtuellen Mappen", den Dossiers. Diese stellen die elektronische Repräsentation einer Papiermappe dar und sind das zentrale Erschließungsobjekt. Im Gegensatz zu statischen Klassifikationssystemen ist die Dossierstruktur dynamisch und aufkommensabhängig, d.h. neue Dossiers werden hauptsächlich anhand der aktuellen Berichterstattung erstellt. Insgesamt enthält die DIZ-Pressedatenbank ca. 90.000 Dossiers, davon sind 68.000 Sachthemen (Topics), Personen und Institutionen. Die Dossiers sind untereinander zum "DIZ-Wissensnetz" verlinkt.

Reiner, U.: Automatische DDC-Klassifizierung von bibliografischen Titeldatensätzen (2009) 0.02

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Date: 22. 8.2009 12:54:24

Automatic classification research at OCLC (2002) 0.01

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Date: 5. 5.2003 9:22:09

Yoon, Y.; Lee, C.; Lee, G.G.: ¬An effective procedure for constructing a hierarchical text classification system (2006) 0.01

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Date: 22. 7.2006 16:24:52

Yi, K.: Automatic text classification using library classification schemes : trends, issues and challenges (2007) 0.01

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Date: 22. 9.2008 18:31:54

Liu, R.-L.: Context recognition for hierarchical text classification (2009) 0.01

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Date: 22. 3.2009 19:11:54

Pfeffer, M.: Automatische Vergabe von RVK-Notationen mittels fallbasiertem Schließen (2009) 0.01

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Date: 22. 8.2009 19:51:28

Mengle, S.; Goharian, N.: Passage detection using text classification (2009) 0.01

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Date: 22. 3.2009 19:14:43

Khoo, C.S.G.; Ng, K.; Ou, S.: ¬An exploratory study of human clustering of Web pages (2003) 0.01

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Date: 12. 9.2004 9:56:22

Reiner, U.: Automatische DDC-Klassifizierung bibliografischer Titeldatensätze der Deutschen Nationalbibliografie (2009) 0.01

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Date: 22. 1.2010 14:41:24

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